一种虚拟核退役环境下多无人车辐射巡测系统设计

冯青林; 胡春鹤; 杜垚垚

doi:10.11884/HPLPB202436.240069

一种虚拟核退役环境下多无人车辐射巡测系统设计

doi: 10.11884/HPLPB202436.240069

1.
北京林业大学工学院，北京市 100083
2.
中国科学院高能物理研究所，北京市 100039

基金项目: 国家自然科学基金项目(61703047).基金项目：国家自然科学基金项目(61703047)

详细信息

作者简介:
胡春鹤，huchunhe@bjfu.edu.cn

杜垚垚，duyy@ihep.ac.cn

通讯作者:
冯青林，18810536737@163.com。

中图分类号: TL75+1;TP242.6
计量
- 文章访问数: 27
- HTML全文浏览量: 16
- PDF下载量: 0
- 被引次数: 0
出版历程
- 收稿日期: 2024-02-29
- 修回日期: 2024-08-27
- 录用日期: 2024-06-24
- 网络出版日期: 2024-10-12

Design of a multi unmanned vehicle radiation monitoring system in a virtual nuclear retirement environment

Feng Qinglin^{1
, ,},
Hu Chunhe^1
,,
Du Yaoyao^2
,

1.
School of Technology, Beijing Forestry University, Beijing 100083, China
2.
The Institute of High Energy Physics of the Chinese Academy of Sciences , Beijing 100039, China

摘要

摘要: 为提高核退役设施辐射测量效率、减少测量人员遭受放射性照射的风险,设计了一种面向多无人车编队辐射巡测控制系统。首先，采用领航-跟随编队策略，控制机器人以预定队形行进，同时实时采集每个无人车在编队行进过程中巡测到的辐射强度信息以及它们各自的位置数据，初步地分析环境内部的辐射分布状况。其次，利用辐射强度与位置信息，运用马尔科夫链蒙特卡洛方法对放射源参数进行估计。仿真结果表明，无人车编队不仅可以在辐射环境下按照自动规划的路径运动并对放射源位置进行参数估计，且行进过程中距离误差为0～0.055 m，观测角误差为0～0.035 rad。
- 核退役环境 /
- 领航跟随法 /
- 无人车编队 /
- 放射源估计 /
- 辐射巡测
Abstract: To improve the radiation measurement efficiency of nuclear retirement facilities and reduce the risk of radiation exposure to measurement personnel, a radiation patrol control system for multiple unmanned vehicle formations has been designed. Firstly, the navigation following formation strategy is adopted to control the robots to move in a predetermined formation, while collecting real-time radiation intensity information and their respective position data measured by each unmanned vehicle during the formation process, to preliminarily analyze the radiation distribution inside the environment. Secondly, utilizing radiation intensity and location information, the Markov chain Monte Carlo method is employed to estimate the parameters of the radiation source. The simulation results show that the unmanned vehicle formation can move along the automatically planned path in a radiation environment, with advantages such as fast response speed, high control accuracy, and can estimate the parameters of the radiation source position coordinates.
- nuclear radiation environment /
- leader-follower /
- unmanned vehicle formation /
- radiation source estimation /
- radiation detection

HTML全文

图 1 核退役环境和辐射分布

Figure 1. Nuclear decommissioning scenarios and radiation distribution

下载: 全尺寸图片幻灯片

图 2 基于距离角度($d - \beta $)领航跟随法的编队模型

Figure 2. Formation model based on $d - \beta $ leader-follower method

下载: 全尺寸图片幻灯片

图 3 改进线性自抗扰编队控制器

Figure 3. Improved linear active disturbance rejection formation control

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图 4 不同编队控制策略下的距离误差

Figure 4. Distance error under different formation control strategies

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图 5 不同编队控制策略下的观测角误差

Figure 5. Observation angle error under different formation control strategies

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图 6 系统仿真平台整体架构

Figure 6. System simulation platform overall architecture

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图 7 Gazebo仿真结果

Figure 7. Simulation results of Gazebo

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表 1 核退役环境无人车主要技术参数

Table 1. Main technical parameters of unmanned vehicles in nuclear decommissioning environment

Main technical parameters of unmanned vehicles in nuclear decommissioning environment
dimensions	wheel diameter	maximum load	battery life	maximum speed	operating temperature	operating humidity	γ detection	LiDAR
dimensions	wheel diameter	maximum load	battery life	maximum speed	operating temperature	operating humidity	γ detection	wavelength	point rate
138 mm178 mm 192 mm	66 mm	15 KG	＞4 h	1 m/s	−20℃−50 ℃	5%−95%	range 0.1 μSv/ h-3 msV/h	905 mm	1.152 MHz

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